Amostras instrumentais¶
import warnings
warnings.simplefilter('ignore')
import IPython.display as ipd
import librosa
%matplotlib inline
import matplotlib.pyplot as plt
import librosa.display
import numpy as np
print('ContraBaixo')
ipd.Audio('../_static/audio/cb.wav')
ContraBaixo
x, sr = librosa.load('../_static/audio/cb.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f625ff5f8e0>
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
print('ContraBaixo e Flauta')
ipd.Audio('../_static/audio/cbfl.wav')
ContraBaixo e Flauta
x, sr = librosa.load('../_static/audio/cbfl.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f625faa7b20>
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
print('Trompa')
ipd.Audio('../_static/audio/fh.wav')
Trompa
x, sr = librosa.load('../_static/audio/fh.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f625f9b0fd0>
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
print('Flauta')
ipd.Audio('../_static/audio/fl.wav')
Flauta
x, sr = librosa.load('../_static/audio/fl.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f625fc05340>
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
print('Harpa')
ipd.Audio('../_static/audio/hp.wav')
Harpa
x, sr = librosa.load('../_static/audio/hp.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f625fd3bee0>
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
print('Harpa e Trompa')
ipd.Audio('../_static/audio/hpfh.wav')
Harpa e Trompa
x, sr = librosa.load('../_static/audio/hpfh.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f625fe6ff70>
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()
print('Mistura')
ipd.Audio('../_static/audio/mistura.wav')
Mistura
x, sr = librosa.load('../_static/audio/mistura.wav', duration=0.02)
plt.figure(figsize=(14, 10))
librosa.display.waveplot(x, sr=sr, alpha=0.8)
<matplotlib.collections.PolyCollection at 0x7f625f916550>
S = librosa.feature.melspectrogram(y=x, sr=sr, n_mels=128,
fmax=8000)
plt.figure(figsize=(14, 5))
S_dB = librosa.power_to_db(S, ref=np.max)
librosa.display.specshow(S_dB, sr=sr, x_axis='time', y_axis='hz')
plt.colorbar(format='%+2.0f dB')
plt.title('Mel-frequency spectrogram')
plt.tight_layout()
plt.show()